Toward usable evidence: Optimizing knowledge accumulation in HCI research on health behavior change

Predrag Klasnja, Eric B. Hekler, Elizabeth V. Korinek, John Harlow, Sonali R. Mishra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Over the last ten years, HCI researchers have introduced a range of novel ways to support health behavior change, from glanceable displays to sophisticated game dynamics. Yet, this research has not had as much impact as its originality warrants. A key reason for this is that common forms of evaluation used in HCI make it difficult to effectively accumulate - and use - knowledge across research projects. This paper proposes a strategy for HCI research on behavior change that retains the field's focus on novel technical contributions while enabling accumulation of evidence that can increase impact of individual research projects both in HCI and the broader behavior-change science. The core of this strategy is an emphasis on the discovery of causal effects of individual components of behavior-change technologies and the precise ways in which those effects vary with individual differences, design choices, and contexts in which those technologies are used.

Original languageEnglish (US)
Title of host publicationCHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
Subtitle of host publicationExplore, Innovate, Inspire
PublisherAssociation for Computing Machinery
Pages3071-3082
Number of pages12
Volume2017-May
ISBN (Electronic)9781450346559
DOIs
StatePublished - May 2 2017
Externally publishedYes
Event2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017 - Denver, United States
Duration: May 6 2017May 11 2017

Other

Other2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017
CountryUnited States
CityDenver
Period5/6/175/11/17

Fingerprint

Human computer interaction
Health
Display devices

Keywords

  • Behavior change
  • Evaluation methods
  • Health informatics
  • User studies

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Klasnja, P., Hekler, E. B., Korinek, E. V., Harlow, J., & Mishra, S. R. (2017). Toward usable evidence: Optimizing knowledge accumulation in HCI research on health behavior change. In CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire (Vol. 2017-May, pp. 3071-3082). Association for Computing Machinery. https://doi.org/10.1145/3025453.3026013

Toward usable evidence : Optimizing knowledge accumulation in HCI research on health behavior change. / Klasnja, Predrag; Hekler, Eric B.; Korinek, Elizabeth V.; Harlow, John; Mishra, Sonali R.

CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire. Vol. 2017-May Association for Computing Machinery, 2017. p. 3071-3082.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Klasnja, P, Hekler, EB, Korinek, EV, Harlow, J & Mishra, SR 2017, Toward usable evidence: Optimizing knowledge accumulation in HCI research on health behavior change. in CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire. vol. 2017-May, Association for Computing Machinery, pp. 3071-3082, 2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017, Denver, United States, 5/6/17. https://doi.org/10.1145/3025453.3026013
Klasnja P, Hekler EB, Korinek EV, Harlow J, Mishra SR. Toward usable evidence: Optimizing knowledge accumulation in HCI research on health behavior change. In CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire. Vol. 2017-May. Association for Computing Machinery. 2017. p. 3071-3082 https://doi.org/10.1145/3025453.3026013
Klasnja, Predrag ; Hekler, Eric B. ; Korinek, Elizabeth V. ; Harlow, John ; Mishra, Sonali R. / Toward usable evidence : Optimizing knowledge accumulation in HCI research on health behavior change. CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire. Vol. 2017-May Association for Computing Machinery, 2017. pp. 3071-3082
@inproceedings{aa0fab803c9b40a4858f4a89b5783d70,
title = "Toward usable evidence: Optimizing knowledge accumulation in HCI research on health behavior change",
abstract = "Over the last ten years, HCI researchers have introduced a range of novel ways to support health behavior change, from glanceable displays to sophisticated game dynamics. Yet, this research has not had as much impact as its originality warrants. A key reason for this is that common forms of evaluation used in HCI make it difficult to effectively accumulate - and use - knowledge across research projects. This paper proposes a strategy for HCI research on behavior change that retains the field's focus on novel technical contributions while enabling accumulation of evidence that can increase impact of individual research projects both in HCI and the broader behavior-change science. The core of this strategy is an emphasis on the discovery of causal effects of individual components of behavior-change technologies and the precise ways in which those effects vary with individual differences, design choices, and contexts in which those technologies are used.",
keywords = "Behavior change, Evaluation methods, Health informatics, User studies",
author = "Predrag Klasnja and Hekler, {Eric B.} and Korinek, {Elizabeth V.} and John Harlow and Mishra, {Sonali R.}",
year = "2017",
month = "5",
day = "2",
doi = "10.1145/3025453.3026013",
language = "English (US)",
volume = "2017-May",
pages = "3071--3082",
booktitle = "CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems",
publisher = "Association for Computing Machinery",

}

TY - GEN

T1 - Toward usable evidence

T2 - Optimizing knowledge accumulation in HCI research on health behavior change

AU - Klasnja, Predrag

AU - Hekler, Eric B.

AU - Korinek, Elizabeth V.

AU - Harlow, John

AU - Mishra, Sonali R.

PY - 2017/5/2

Y1 - 2017/5/2

N2 - Over the last ten years, HCI researchers have introduced a range of novel ways to support health behavior change, from glanceable displays to sophisticated game dynamics. Yet, this research has not had as much impact as its originality warrants. A key reason for this is that common forms of evaluation used in HCI make it difficult to effectively accumulate - and use - knowledge across research projects. This paper proposes a strategy for HCI research on behavior change that retains the field's focus on novel technical contributions while enabling accumulation of evidence that can increase impact of individual research projects both in HCI and the broader behavior-change science. The core of this strategy is an emphasis on the discovery of causal effects of individual components of behavior-change technologies and the precise ways in which those effects vary with individual differences, design choices, and contexts in which those technologies are used.

AB - Over the last ten years, HCI researchers have introduced a range of novel ways to support health behavior change, from glanceable displays to sophisticated game dynamics. Yet, this research has not had as much impact as its originality warrants. A key reason for this is that common forms of evaluation used in HCI make it difficult to effectively accumulate - and use - knowledge across research projects. This paper proposes a strategy for HCI research on behavior change that retains the field's focus on novel technical contributions while enabling accumulation of evidence that can increase impact of individual research projects both in HCI and the broader behavior-change science. The core of this strategy is an emphasis on the discovery of causal effects of individual components of behavior-change technologies and the precise ways in which those effects vary with individual differences, design choices, and contexts in which those technologies are used.

KW - Behavior change

KW - Evaluation methods

KW - Health informatics

KW - User studies

UR - http://www.scopus.com/inward/record.url?scp=85027442622&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85027442622&partnerID=8YFLogxK

U2 - 10.1145/3025453.3026013

DO - 10.1145/3025453.3026013

M3 - Conference contribution

AN - SCOPUS:85027442622

VL - 2017-May

SP - 3071

EP - 3082

BT - CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

ER -